Python ML_GenAI Engineers

We are seeking a Junior AI Engineer to design, build, and deploy enterprise-grade Generative AI applications leveraging cloud-native architectures and modern LLM ecosystems. The ideal candidate will have strong data engineering foundations combined with expertise in Retrieval-Augmented Generation (RAG), agentic workflows, and AI service integration.

Responsibilities

1. Design and develop GenAI applications using Python and enterprise LLM platforms.

2. Build scalable data pipelines for structured and unstructured data processing.

3. Implement Retrieval-Augmented Generation (RAG) systems and vector-based search solutions.

4. Integrate LLMs with enterprise applications through APIs and workflows.

5. Develop cloud-native AI services on AWS, Azure, GCP, Databricks (DBRX), or Snowflake.

6. Create agent-based solutions using LangChain and LangGraph.

7. Ensure data quality, governance, and security compliance across AI workflows.

8. Optimize performance, scalability, and reliability of AI solutions.

Technical requirements

Python, SQL, ETL/ELT, Data Modeling, Data Quality, Cloud-native Development, API Integration, Data Engineering, ETL, Document Processing, Workflow design, knowledge of LLM development, RAG, Prompt Engineering, AI Coding Assistants

Advanced Skills:

RAG Data Pipelines, LLM Data Integration, AI Service Integration, Scalable AI Deployments, Agent Orchestration, Tool Calling, LangGraph, LangChain

Additional responsibilities

1. 1+ years of experience with Hugging Face, LangChain, OpenAI, Anthropic, Gemini, or open-source LLMs.

2. Familiarity with knowledge graphs and semantic search.

3. Experience building production-grade GenAI solutions

Preferred skills

Technology->AI-Data science->Machine Learning,Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)

Education

Bachelor of Engineering